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When I applied the modularity dichotomy to smartphone operating system there were several implications that came to light. One was the question of whether the market has reached the point where products were “good enough” and the speed of innovation became less important than price. Another was: will integrated vendors be able to hold on to a healthy share of growth against non-consumption?

Now I bring up another implication of modularity: the concept of “law of conservation of modularity”.

Horace discusses his latest work at the Christensen Institute and considers why the educational system works the way it does. Can large scale education be modularized? In the second half of the show, Anders and Horace discuss the rumors about the possibility that Apple might be working on a car.

Understanding Apple’s intentions seems to be a popular parlor game and there are many attempts at divining intention from data and market study. These attempts at market research for answers are futile because Apple does not compete in existing markets but rather it creates new markets. For instance, the market for the Apple II could not have been assessed from research into the computing market of 1974. The intention for Apple to enter into music devices and services could not have been predicted through an analysis of MP3 player market in 2000. The iPhone was also not predicated on the market for “Internet Communicators” in 2006 or 2002 when the iPad was first contemplated.[1]

Instead of measuring the size of pre-existing markets, surveying the functionality of existing products, or weighing toxically financialized ratios like margins and market shares, I recall this ad (Our Signature, first seen at 2013 WWDC):

This is it
This is what matters

The experience of a product
How it will make someone feel
Will it make life better?
Does it deserve to exist?

We spend a lot of time on a few great things
Until every idea we touch
Enhances each life it touches

You may rarely look at it
But you will always feel it
This is our signature
And it means everything

My interpretation of these lines, coupled with additional public statements can be used to create a “litmus test” for new product categories:

1. The experience of a product. Read: They will work on things to which they can make a meaningful contribution. To me this means that they will build things which require an integrated approach. As Apple is “the last integrated company standing” it means they will work on problems where the system is not good enough. This means that they will not work on problems where an individual modular component is not good enough. By system I mean, in the largest sense: production, design, distribution, sales, support and services must work in a seamless way. Systems analysis implies a broad understanding of the causes of insufficient performance along the dimensions of “experience”. The experiences are what differentiate the products (and lead to high margins) and these experiences are possible only through the control of interdependent modules.

2. Does it deserve to exist? Read: They will work on very few things. They will say no to many things. It’s still true that all of Apple’s products can fit on one table. That may not be true forever, but their product space will not grow as quickly as sales grow. This means that there is no notion of “marginal value” or portfolio theory where products are added because they can be justified as “moving the needle” or balancing demand. Rather, the few things which will be worked on will address non-consumption. Non-consumption of experiences.

3. Enhance life. Read: The things they release are inevitable even though nobody asked for them. The reason this is possible is that there are unmet and unidentified “jobs to be done” which are powerful sources of demand and whose satisfaction leads to unforeseen rewards. The problems that can be addressed are uncovered through a process of conversation with a few people. They are not uncovered through surveys or large n statistical studies. Without the ability to ask the right questions, big data only leads to big misdirection. In contrast, good taste in questions allows small n to lead to big insight. Apple’s ability for finding the right problem to solve comes from this greatness of taste in questions.

So given this litmus test, will Apple build a Car?

I believe the problem of transportation and its proxy, the automobile, provide all the requisite demand for Apple’s attention. Technical questions abound and they may still prove unsurmountable before a launch happens, but there are no doubts in my mind that this is a problem Apple would see fit to address.

Non-consumption of unmet and unarticulated jobs to be done can and should be addressed with systems solutions and new experiences.

The poetry is pretty clear on the matter.

Notes:

The market for phones was large but the iPhone pricing and features made it incompatible with any reasonable segment of it. [↩]

The Auto Industry is significant. With gross revenues of over $2 trillion, production of over 66 million vehicles and growing[1] it seems to be a big, juicy target. It employs 9 million people directly and 50 million indirectly and politically it must rank among the top three industries worthy of government subsidy (or interference). Indeed, in many countries–the US included–government interference makes it practically impossible for a producer to go out of business, no matter how poorly it’s managed or how untenable the market conditions.

But this might be the tell-tale sign that danger lurks. Theory suggests that incumbents going out of business is an essential indicator of industry health. Without their exit, entrants are never allowed to bring disruptive ideas to bear and innovation simply stops. Is this interference with mortality the only indication of entrant obstacles? Are things about to change? Is there pressure for innovation? Can we spot other indications of a crisis in this industry?

Taking the US as a proxy, here is a graph of the number of new car firm entries (and exits):

The total number of firms[2] that entered the US market is 1,556. The blue line graph shows the entries and the orange line shows the exits. This sounds impressive, but note that the year when the peak of entries took place was 1914, exactly 100 years ago.

Notes:

The industry continues to grow, registering a 30 percent increase over the past decade, mainly due to Asia and China in particular [↩]

As corporate romances go, IBM and Apple’s must rank among the most unexpected. As I wrote on the date they changed their Facebook status, the two companies were antagonists for the better part of twenty years and their rapprochement was met with a shrug mostly because yet more decades passed since.

Nostalgia aside, this new union is profoundly important. It indicates and evidences change on a vast scale. The companies’ antagonism was due to being once aimed at the same business: computing. Since the early 1980s, “computing” came to be modularized into hundreds, perhaps thousands of business models. It is no longer as simple as selling beige boxes. IBM was forced out of building computers and into services and consulting while Apple moved to make devices and the software and services which make its hardware valuable.

The convergence of interests which was consummated into a deal this year stems from the migration of computing around what has come to be called “mobile”. Apple intends to accelerate the adoption of its mobile platforms among the remaining non-adopters: enterprises–a group which, by now, qualifies as laggards.[1] Simultaneously IBM intends to connect data warehouses at those same enterprises to their employed users.

Notes:

There was a time–when Apple was young–when enterprises were the innovators, early adopters. That role ended approximately in the year 2000 [↩]

Part I is a review of the “automotive stack” and note how there is no singular event that seems to affect disruptive change. From changing jobs to be done, modular design and manufacturing processes, powertrain evolution, urbanization, environmental interests, regulation and taxation.

Part II is a review of a framework of analysis based on sources and uses of energy. Inputs, efficiency/losses, network effects and inertia, what can change and what can’t change.

For a shot of theory, Horace reflects on the dichotomy of efficiency vs. efficacy when it comes to predicting change in the sector.

[It’s important to understand just how much the theory has evolved in the last 10 years. Much more perhaps than in its first eight.]

Doug Kaye: Hello, and welcome to IT Conversations, a series of interviews recording and transcripts on the hot topics of information technology. I am your host, Doug Kaye, and in today’s program, I am pleased to bring you this special presentation from the Open Source Business Conference held in San Francisco on March 16 and 17, 2004.

Mike Dutton: My name is Mike Dutton, and it is my pleasure to introduce to you today Clayton Christensen. Professor Christensen hardly needs an introduction. His first bestseller, “The Innovator’s Dilemma,” has sold over half a million copies and has added the terms “disruptive innovation” to our corporate lexicon. His sequel — and you have to have a sequel to be a management guru — is entitled “The Innovator’s Solution” and is currently Business Week’s bestseller’s list. Professor Christensen began his career at the Boston Consulting Group and served as a White House fellow in the Reagan administration. In 1984, he cofounded and served as chairman of Ceramics Process Systems Cooperation. Then, as he was approaching his 40th birthday, he took the logical step of quitting his job and going back to school, where he earned a doctorate in Business Administration from Harvard Business School. So, today he is a professor of Business Administration at Harvard Business School where teaches and researches technology commercialization innovation. Professor Christensen is also a practicing entrepreneur. In 2000 he founded Innosight, a consulting firm focused on helping firms set their innovative strategies. And according to a recent article in Newsweek, “Innosight’s phones ring off the hook, and the firm cannot handle all the demand,” very similar to all the startups in open source here today. So, please join me in welcoming Clayton Christensen.

Clayton Christensen: Thank you, Mike! I’m 6 feet 8, so if it’s okay, I’ll just…the mic picks up okay. I’m sure delighted to be with you, especially because there is blizzard in Boston today; my kids have to shovel the snow!

As Mike mentioned, I came in to academia late in life, and the first chunk of research that I was engaged in was trying to understand what it is that could kill a successful, well — run company. And those of you who are familiar with it, probably know that the odd conclusion that I got of that was that it was actually good management that kills these companies. And subsequent then to the publishing of the book that summarized that work, “The Innovator’s Dilemma,” I’ve been trying to understand the flip side of that, which is if I want to start a new business that has the potential to kill a successful, well — run competitor, how would I do it? And that’s what we tried summarize in the book, “The Innovator’s solution.” It’s really quite a different book than the “Dilemma” was, because the “Dilemma” built a theory of what is it that caused these companies to fail. And then in the writing of this solution, I’ll just give you analogy for where we came out on how to successfully start new growth businesses.

I remember when I first got out of business school and had my first job. I was taught the methods of total quality management as they existed in the 1970’s, and we had this tool that was called a “statistical process control chart.” (Do they still teach that around here?) Basically you made a piece, you measured the critical performance parameter and you plotted it on this chart, and there was a target parameter that you were always trying to make the piece to hit, but you had this pesky scatter around that target. And I remember being taught at the time that the reason for the scatter is that there is just intrinsic variability and unpredictability in manufacturing processes.

So, the methods that were taught about manufacturing quality control in the ‘70’s were all oriented to helping you figure out how to deal with that randomness. And then the quality movement came of age, and what they taught us is, “No, there’s not randomness in manufacturing processes.” Every time you got a result that was bad, it actually had a cause, but it just appeared to be random because you didn’t know what caused it. And so the quality movement then gave us tools to understand what are all the different variables that can affect the consistency of output in a manufacturing operation. And once we could understand what those variables were and then develop methods to control them, manufacturing became not a random process, but something that was highly predictable and controllable.

There are 7.1 billion people on Earth. Coincidentally there are also 7 billion mobile connections. Those connections are held by 3.45 billion unique mobile subscribers.[1] Unsurprisingly, the largest national mobile markets (by number of subscriptions) correspond closely to the most populous nations.

Considering smartphones, last year 1 billion smartphones were sold and the number of smartphones in use is about 2 billion[2]

Given the rapid adoption of smartphones, it’s also safe to assume that smartphone penetration will follow population distribution. In the US, where comScore data is published monthly, penetration is following a predictable logistic curve.

Assuming similar patterns world-wide we can forecast regional smartphone penetration.

Put another way: Why is it that everyone wants to copy Apple’s products but nobody wants to copy being Apple?

Being Apple means, at least:

Insourcing all aspects of operations which affect the customer experience. Increasingly that has meant insourcing everything, a toxic idea to every MBA-trained professional since forever.

Organizing functionally and having no product level P/L responsibility. That also means removing almost all incentives for employees to climb ladders and thus prove their worth.

Developing products using integrated “heroic” efforts which shun every best (or even adequate) process for product development.

I asked somewhat rhetorically because it’s an open question. Apple’s operating model and devotion to integration have been asymmetric to technology dogma for decades. To the casual (read: naïve) observer, pursuing the Apple way seemed also to be tied to one individual. You could not “be Apple” unless you were also Steve Jobs and there was only one of him.

Horace Dediu and Jim Zellmer discuss the pleasures of traversing continents by road. This leads to a grand tour of powertrains, composites, fuel efficiency, regulation and Tesla’s luxury market entry. Which naturally leads to a conversation on emerging auto modularization, apps and ecosystems and where value will accrue.